Results 1 to 10 of about 83,751 (262)

A New Method for Least-Squares and Minimax Group-Delay Error Design of Allpass Variable Fractional-Delay Digital Filters

EURASIP Journal on Advances in Signal Processing, 2010
A double-loop iterative method is proposed to design allpass variable fractional-delay (VFD) digital filters basing on the minimization of root-mean-squared group-delay error. In the inner loop, an iterative quadratic optimization is proposed to replace
Pei Soo-Chang, Shyu Jong-Jy, Chan Cheng-Han   +2 more
doaj  

Machine Learning and Shapley Additive Explanations Value Integration for Predicting the Prognostic of Anti-N-Methyl-D-Aspartate Receptor Encephalitis: Model Development and Evaluation Study

JMIR Medical Informatics
BackgroundAnti-N-methyl-D-aspartate receptor (NMDAR) encephalitis is a rare disease with no accurate prognostic tools to predict the prognosis of patients. ObjectiveThis study aims to develop an interpretable machine learning model using real-
Jia Wang, Haotian Wu, Han Cai, YingXiang Wang, Jian Gu   +4 more
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MS-YieldStackNet: multi-source data fusion for wheat yield estimation using a stacked ensemble neural network [PDF]

PeerJ Computer Science
Accurate crop yield prediction is vital for ensuring food security and informing agricultural policy, particularly in wheat-dependent regions like Pakistan where manual estimation methods are labor-intensive and imprecise.
Waqas Ali, Zeeshan Ramzan, Muhammad Shahbaz, Qamar Ul Zaman Bhutta, Muhammad Talha, Mohammed J. AlGhamdi   +5 more
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Advancing sustainable renewable energy: XGBoost algorithm for the prediction of water yield in hemispherical solar stills

Discover Sustainability
The increasing demand for clean water necessitates innovative approaches to optimize water productivity through renewable energy systems. This study harnessed computer science-based algorithm to forecast the productivity of hemispherical solar stills ...
Salwa Ahmad Sarow, Hasan Abbas Flayyih, Maryam Bazerkan, Luttfi A. Al-Haddad, Zainab T. Al-Sharify, Ahmed Ali Farhan Ogaili   +5 more
doaj   +1 more source

Native AI-based hybrid deep learning for wireless link quality prediction in NTN waterside scenarios

ICT Express
Predicting link quality before establishing communication between transmitter and receiver enhances channel selection. With the advancements in artificial intelligence, prediction is now possible for complex environments such as riverside, maritime and ...
Shrutika Sinha, G. Pradeep Reddy, Sea-Moon Kim, Soo-Hyun Park   +3 more
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“Smart agriculture: a climate-driven approach to modelling and forecasting fall armyworm populations in maize using machine learning algorithms”

Frontiers in Plant Science
The fall armyworm (Spodoptera frugiperda) poses a significant threat to global maize production owing to its rapid life cycle, extensive host range, and strong dispersal capabilities. We developed a forecasting system for fall armyworm outbreaks over one
Vani Sree Kalisetti, Upendhar Sudharshanam, Nagesh Kumar Mallela Venkata, Rajashekhar Mandla, Srinivas Akula, Mallaiah Bedika, Bhadru Dharavath, Sreelatha Dogga, Ramakrishna Babu A, Chandrasekhar Javaji   +9 more
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A fixed count sampling estimator of stem density based on a survival function

Journal of Forest Science, 2015
In fixed count sampling (FCS) a fixed number (k) of observations is made at n randomly selected sample locations. For estimation of stem density, the distance from a random sample location to the k nearest trees was measured.
S. Magnussen
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River stream flow prediction through advanced machine learning models for enhanced accuracy

Results in Engineering
The Narmada River basin, a significant water resource in central India, plays a crucial role in supporting agricultural, industrial, and domestic water supply.
Naresh Kedam, Deepak Kumar Tiwari, Vijendra Kumar, Khaled Mohamed Khedher, Mohamed Abdelaziz Salem   +4 more
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A Hybrid Model XBORE for Predicting the Performance of Truck-Haulage Systems in the Ore Transportation Process at Underground Mine

IEEE Access
Most mining companies worldwide endeavor to promote the continued flow of ore at every mining stage to ensure the mines’ productivity and profitability.
Morris Mkokweza, Santhi Kumaran, George Mufungulwa, Omar Haji Kombo   +3 more
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Research on Ship Trajectory Prediction Method Based on CNN-RGRU-Attention Fusion Model

IEEE Access
Based on Automatic Identification System (AIS) data in maritime settings, this paper explores the limitations of traditional Recurrent Neural Networks in extracting features from complex vessel trajectory sequences.
Wei Liu, Yu Cao, Meng Guan, Linlin Liu
doaj   +1 more source